How BestDish works

Short version: we blend Google review strength (rating pulled toward a 3.8 baseline, weighted by review-count volume) with community-mention scoring mined from Reddit threads, editorial guides and YouTube reviews. Money never changes a ranking, global fast-food chains are excluded, and venues need 30+ Google reviews to qualify.

Sources

The scoring formula

Review-strength score (all pages), using an IMDb-style weighted rating so low review counts get pulled toward the city average rather than trusted at face value:

google_score = max(0, (rating − 3.8) / 1.2) × (log10(max(reviews, 10)) / 4) × 100

Community-mention score (mined pages):

mention_score = reddit_mentions × 10 + "the best" superlatives × 6 + editorial inclusions × 8 + YouTube mentions × 7

Blended (current, v2.0): with review-text data, 0.55 × community + 0.25 × review-text dish-praise + 0.20 × review-strength; without review-text data yet, 0.70 × community(×confidence) + 0.30 × review-strength; un-mined pages use review-strength only. Community evidence is weighted highest because star ratings cluster around 4★ and are gameable — what locals repeatedly say about a specific dish is the strongest signal we have.

What's excluded

• Global fast-food and dessert chains (McDonald's, KFC, Domino's, Starbucks, …) — the site finds local specialists, not chains you already know
• Venues with fewer than 30 Google reviews (too little signal)
• Money never changes a ranking; any paid placement would be labelled and sit outside the ranked list

Freshness

Venue data refreshes monthly via the Places API; the "Updated" line and sitemap lastmod change with every rebuild. Mining re-runs each refresh; flagship pages are re-curated by hand when materially stale.

Known limitations — honest list

1. Mining can only re-rank venues already in Google's top-20 results — a community favourite Places doesn't surface can't appear yet.
2. Auto-mining is a string-match tally on public text — it can't read sarcasm or "used to be good"; flagship pages get human curation instead.
3. Suburb tags are parsed from addresses — occasional oddities are possible.
4. Google ratings carry some chain/tourist bias — mitigated by the baseline+log formula, chain exclusion, and the community/rating blend.

Who's behind this

BestDish is an independent Australian editorial project — no venue pays for a spot, no listing is sponsored. Corrections or tips: hello@bestdish.io.

Corrections & affiliate disclosure

Corrections policy: every ranking is computed from public data, but the inputs (an address, a venue's open/closed status, a mis-attributed mention) can be wrong. Tell us at hello@bestdish.io with a link or screenshot backing the correction; verified fixes are made within 5 business days and the page's "Updated" date and sitemap lastmod change to reflect it. Corrections are never made for money — only for accuracy.

Affiliate / advertising disclosure: BestDish carries no paid placements, sponsorships or affiliate links today. If that ever changes, any commercial link will be clearly labelled "Sponsored" or "Affiliate", will sit outside the ranked list, and will never be able to raise a venue's score, rank or evidence — money never changes a ranking, full stop.

Legal

Ratings and review counts © Google (Places API, attributed on every page). Rankings are editorial opinion computed from public data; no personal data is collected beyond an optional subscribe email; venue trademarks belong to their owners.